Abstract
We have developed a new kinetic model to study how microbial dynamics are affected by the heterogeneity in the physical structure of the environment and by different strategies for hydrolysis of polymeric carbon. The hybrid model represented the dynamics of substrates and enzymes using a continuum representation and the dynamics of the cells were modeled individually. Individual-based biological model allowed us to explicitly simulate microbial diversity, and to model cell physiology as regulated via optimal allocation of cellular resources to enzyme synthesis, control of growth rate by protein synthesis capacity, and shifts to dormancy. This model was developed to study how microbial community functioning is influenced by local environmental conditions in heterogeneous media such as soil and by the functional attributes of individual microbes. Microbial community dynamics were simulated at two spatial scales: micro-pores that resemble 6–20-μm size portions of the soil physical structure and in 111-μm size soil aggregates with a random pore structure. Different strategies for acquisition of carbon from polymeric cellulose were investigated. Bacteria that express membrane-associated hydrolase had different growth and survival dynamics in soil pores than bacteria that release extracellular hydrolases. The kinetic differences suggested different functional niches for these two microbe types in cellulose utilization. Our model predicted an emergent behavior in which co-existence of membrane-associated hydrolase and extracellular hydrolases releasing organisms led to higher cellulose utilization efficiency and reduced stochasticity. Our analysis indicated that their co-existence mutually benefits these organisms, where basal cellulose degradation activity by membrane-associated hydrolase-expressing cells shortened the soluble hydrolase buildup time and, when enzyme buildup allowed for cellulose degradation to be fast enough to sustain exponential growth, all the organisms in the community shared the soluble carbon product and grew together. Although pore geometry affected the kinetics of cellulose degradation, the patterns observed for the bacterial community dynamics in the 6–20 μm-sized micro-pores were relevant to the dynamics in the more complex 111-μm-sized porous soil aggregates, implying that micro-scale studies can be useful approximations to aggregate scale studies when local effects on microbial dynamics are studied. As shown with examples in this study, various functional niches of the bacterial communities can be investigated using complex predictive mathematical models where the role of key environmental aspects such as the heterogeneous three-dimensional structure, functional niches of the community members, and environmental biochemical processes are directly connected to microbial metabolism and maintenance in an integrated model.
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References
Allison SD (2005) Cheaters, diffusion and nutrients constrain decomposition by microbial enzymes in spatially structured environments. Ecol Lett 8:626–635
Allison SD, Martiny JBH (2008) Resistance, resilience, and redundancy in microbial communities. Proc Natl Acad Sci U S A 105:11512–11519
Anderson TH, Domsch KH (1985) Determination of ecophysiological maintenance carbon requirements of soil-microorganisms in a dormant state. Biol Fertil Soils 1(2):81–89
Anderson TH, Domsch KH (1985) Maintenance carbon requirements of actively metabolizing microbial populations under in situ conditions. Soil Biol Biochem 17(2):197–203
Azam F, Malfatti F (2007) Microbial structuring of marine ecosystems. Nat Rev Microbiol 5(10):782–791
Baloo S, Ramkrishna D (1991) Metabolic regulation in bacterial continuous cultures. 2. Biotechnol Bioeng 38(11):1353–1363
Baloo S, Ramkrishna D (1991) Metabolic regulation in bacterial continuous cultures. 1. Biotechnol Bioeng 38(11):1337–1352
Berg HC (1993) Random walks in biology. Princeton University Press, Princeton
Bratbak G, Dundas I (1984) Bacterial dry-matter content and biomass estimations. Appl Environ Microbiol 48(4):755–757
Cambier C, Bousso M, Masse D, Perrier E (2007) A new, offer versus demand, modelling approach to assess the impact of micro-organisms spatio-temporal population dynamics on soil organic matter decomposition rates. Ecol Model 209(2–4):301–313
Chenu C, Roberson EB (1996) Diffusion of glucose in microbial extracellular polysaccharide as affected by water potential. Soil Biol Biochem 28(7):877–884
Creagh AL, Ong E, Jervis E, Kilburn DG, Haynes CA (1996) Binding of the cellulose-binding domain of exoglucanase cex from cellulomonas fimi to insoluble microcrystalline cellulose is entropically driven. Proc Natl Acad Sci U S A 93(22):12229–12234
Dethlefsen L, Schmidt TM (2007) Performance of the translational apparatus varies with the ecological strategies of bacteria. J Bacteriol 189(8):3237–3245
Di Mattia E, Grego S, Cacciari I (2002) Eco-physiological characterization of soil bacterial populations in different states of growth. Microb Ecol 43(1):34–43
Dorodnikov M, Blagodatskaya E, Blagodatsky S, Fangmeier A, Kuzyakov Y (2009) Stimulation of r- vs. K-selected microorganisms by elevated atmospheric co2 depends on soil aggregate size. FEMS Microbiol Ecol 69(1):43–52
Ensign JC (1970) Long-term starvation survival of rod and spherical cells of arthrobacter crystallopoietes. J Bacteriol 103(3):569–577
Fansler SJ, Smith JL, Bolton H, Bailey VL (2005) Distribution of two c cycle enzymes in soil aggregates of a prairie chronosequence. Biol Fertil Soils 42:17–23
Ginovart M, Lopez D, Gras A (2005) Individual-based modelling of microbial activity to study mineralization of c and n and nitrification process in soil. Nonlinear Analysis-Real World Applications 6(4):773–795
Gupta S, Pilyugin SS, Narang A (2005) The dynamics of single-substrate continuous cultures: the role of ribosomes. J Theor Biol 232(4):467–490
Hassink J, Bouwman LA, Zwart KB, Brussaard L (1993) Relationships between habitable pore-space, soil biota and mineralization rates in grassland soils. Soil Biol Biochem 25(1):47–55
Hellweger FL (2008) Spatially explicit individual-based modeling using a fixed super-individual density. Comput Geosci 34:144–152
Hellweger FL, Bucci V (2009) A bunch of tiny individuals-individual-based modeling for microbes. Ecol Model 220(1):8–22
Huang AA (1975) Kinetic studies on insoluble cellulose-cellulase system. Biotechnol Bioeng 17(10):1421–1433
Kjelleberg S, Albertson N, Flardh K, Holmquist L, Jouperjaan A, Marouga R et al (1993) How do nondifferentiating bacteria adapt to starvation. Antonie Van Leeuwenhoek International Journal of General and Molecular Microbiology 63(3–4):333–341
Konopka A (2000) Microbial physiological state at low growth rate in natural and engineered ecosystems. Curr Opin Microbiol 3(3):244–247
Kreft JU, Booth G, Wimpenny JW (1998) Bacsim, a simulator for individual-based modelling of bacterial colony growth. Microbiology 144(Pt 12):3275–3287
Kreft JU, Picioreanu C, Wimpenny JW, van Loosdrecht MC (2001) Individual-based modelling of biofilms. Microbiology 147(Pt 11):2897–2912
Lu YP, Zhang YHP, Lynd LR (2006) Enzyme-microbe synergy during cellulose hydrolysis by clostridium thermocellum. Proc Natl Acad Sci U S A 103(44):16165–16169
Lynd LR, Weimer PJ, van Zyl WH, Pretorius IS (2002) Microbial cellulose utilization: fundamentals and biotechnology. Microbiology and Molecular Biology Reviews 66(3):506
Masse D, Cambier C, Brauman A, Sall S, Assigbetse K, Chotte JL (2007) Mior: an individual-based model for simulating the spatial patterns of soil organic matter microbial decomposition. Eur J Soil Sci 58(5):1127–1135
Moorhead DL, Sinsabaugh RL (2000) Simulated patterns of litter decay predict patterns of extracellular enzyme activities. Appl Soil Ecol 14(1):71–79
Moorhead DL, Sinsabaugh RL (2006) A theoretical model of litter decay and microbial interaction. Ecol Monogr 76(2):151–174
Moorhead DL, Sinsabaugh RL, Linkins AE, Reynolds JF (1996) Decomposition processes: modelling approaches and applications. Sci Total Environ 183(1–2):137–149
Nunan N, Wu K, Young IM, Crawford JW, Ritz K (2002) In situ spatial patterns of soil bacterial populations, mapped at multiple scales, in an arable soil. Microb Ecol 44(4):296–305
O'Donnell AG, Young IM, Rushton SP, Shirley MD, Crawford JW (2007) Visualization, modelling and prediction in soil microbiology. Nat Rev Microbiol 5(9):689–699
Or D, Smets BF, Wraith JM, Dechesne A, Friedman SP (2007) Physical constraints affecting bacterial habitats and activity in unsaturated porous media—a review. Adv Water Res 30:1505–1527
Panikov NS (1991) A synthetic chemostat model as a means of describing the complex behavior of microorganisms. Microbiology 60:299–307
Panikov NS (1995) Microbial growth kinetics. Chapman and Hall, London
Panikov NS, Sizova MV (1996) A kinetic method for estimating the biomass of microbial functional groups in soil. J Microbiol Methods 24(3):219–230
Peth S, Horn R, Beckmann F, Donath T, Fischer J, Smucker AJM (2008) Three-dimensional quantification of intra-aggregate pore-space features using synchrotron-radiation-based microtomography. Soil Sci Soc Am J 72(4):897–907
Pianka ER (1970) R-selection and k-selection. American Naturalist 104(940):592
Resat H, Costa MN, Shankaran H (2011) Spatial aspects in biological system simulations. In: Johnson ML, Brand L (eds) Methods in enzymology: Computer methods, part c. Elsevier, p. 485–511
Salyers AA, Reeves A, Delia J (1996) Solving the problem of how to eat something as big as yourself: diverse bacterial strategies for degrading polysaccharides. J Ind Microbiol Biotechnol 17(5–6):470–476
Sinsabaugh RL, Lauber CL, Weintraub MN, Ahmed B, Allison SD, Crenshaw C et al (2008) Stoichiometry of soil enzyme activity at global scale. Ecol Lett 11(11):1252–1264
Six J, Bossuyt H, Degryze S, Denef K (2004) A history of research on the link between (micro)aggregates, soil biota, and soil organic matter dynamics. Soil Tillage Res 79:7–31
Sleutel S, Cnudde V, Masschaele B, Vlassenbroek J, Dierick M, Van Hoorebeke L et al (2008) Comparison of different nano- and micro-focus x-ray computed tomography set-ups for the visualization of the soil microstructure and soil organic matter. Computers and Geosciences 34(8):931–938
Smith JL (1989) Sensitivity analysis of critical parameters in microbial maintenance-energy models. Biol Fertil Soils 8(1):7–12
Stenstrom J, Svensson K, Johansson M (2001) Reversible transition between active and dormant microbial states in soil. FEMS Microbiol Ecol 36(2–3):93–104
Strong DT, De Wever H, Merckx R, Recous S (2004) Spatial location of carbon decomposition in the soil pore system. Eur J Soil Sci 55(4):739–750
van Bodegom P (2007) Microbial maintenance: a critical review on its quantification. Microb Ecol 53(4):513–523
van Loosdrecht MCM, Lyklema J, Norde W, Zehnder AJB (1990) Influence of interfaces on microbial activity. Microbiol Rev 54(1):75–87
Vlachos C, Paton RC, Saunders JR, Wu QH (2005) A rule-based approach to the modelling of bacterial ecosystems. Biosystems 84(1):49–72
Young IM, Crawford JW (2004) Interactions and self-organization in the soil-microbe complex. Science 304(5677):1634–1637
Acknowledgments
The research described in this paper was funded by the Microbial Communities Initiative LDRD Program at the Pacific Northwest National Laboratory, a multiprogram national laboratory operated by Battelle for the US Department of Energy under Contract DE-AC06-76RL01830. We thank Tim Scheibe and Fred Brockman for useful discussions.
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Resat, H., Bailey, V., McCue, L.A. et al. Modeling Microbial Dynamics in Heterogeneous Environments: Growth on Soil Carbon Sources. Microb Ecol 63, 883–897 (2012). https://doi.org/10.1007/s00248-011-9965-x
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DOI: https://doi.org/10.1007/s00248-011-9965-x